TL;DR: Don’t ask AI agents for one output. Ask for a dozen, each in the style of an expert. Share what works best.

AI agents build apps, analyze data, and visualize it surprisingly well, these days.

We used to tell LLMs exactly what to do. If you’re an expert, this is still useful. An expert analyst can do better analyses than an AI agent. An expert designer or data visualizer can tell an AI agent exactly how to design it.

But you’re not an expert in everything.

Instead, “style transfer” experts.

LLMs are trained on the styles of experts across the world. Tell them to adopt an expert’s style. That’s a shortcut to improve output quality. It won’t be as good as that expert, but likely better than you.

For example, Linux Foundation leaderboards evaluates open source projects - are they active, who’s behind it, do they follow security best practices, what’s their popularity, etc.

Varun use GitHub Copilot with GPT-5 mini to scrape the data Then, he had Claude Opus 4.5 create data visualizations in five different styles:

  1. A Wall Street Journal style. Prompt
  2. Malcolm Gladwell + NYT style, i.e. written in Malcolm Gladwell’s voice (who writes for the New Yorker), but with the New York Times’ visual style. This ability to remix is powerful. Prompt
  3. The Polygraph / The Pudding style. We aren’t specifying a single publication here, but providing multiple publications, allowing it to mix and match from those. Prompt
  4. From Shirley Wu, who is a data artist, allowing us to go to the style of a specific individual. Prompt
  5. An “open source data adventure”. That’s not a publication or a person, but a theme. Prompt

Same input. Five different styles.

For example, while The New York Times comes up with transitional scatter plots (which are great for rich interactive explorations):

… Shirley Wu comes up with these hidden gems, focusing on the smaller projects that have a remarkably diverse contributor base.

Or, while The Wall Street Journal opens with the state of the economy:

The open-source software that underpins trillions of dollars in global commerce is showing signs of strain.

… Malcolm Gladwell opens with perspective:

In the spring of 2023, a small project called CBT Tape caught my attention. Three contributors. That’s it. Yet they had pushed 3,414 commits in twelve months—a rate of 1,138 commits per person. To put that in perspective: a “normal” project sees perhaps 20-30 commits per contributor annually.

At least for the next few years, the ROI is less from expertise. It’s more from style.

Try out different styles. Learn to guide AI towards your preferences. Pick what works best.

And share!